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2.
Tag
Source level (SL)
Sea water
Transmission
loss (TL)
Hydrophone
Sensitivity (RVS)
Signal
Conditioning
gain (G)
Tone detection
a) PLL or
b) Correlation
A B C
Fig. 2. (A)A tag with the exposed circuit. On the left, two transducers are available for communication and on the right side the circuit with the battery is
shown. (B) The sensors and housing are shown as an assembled hydrophone. The circuit on (C) is the part of the hydrophone that ﬁlters, detects and extracts
the tone from the noise. The microcontroller is the i.c. on the lower right corner of the board.
signal at the surface. The block diagram in ﬁgure 2 describes
the undergoing communication process from transmission to
reception for tag detection.
Lead zirconate titanate (PZT) electroacoustic transducers
(Noliac, Denmark) were used. Their frequency response can
be measured by their impedance and is shown in ﬁgure 3.
Two different geometries were used for comparison. Both are
ring shaped transducers with outer diameter of 12.5mm and
wall thickness of 1mm; one is 9mm long and the other one
is 3mm. Noticeable is the marked resonance (fr) and anti-
resonance (fa) frequencies of the transducers when measured
in air. These values are fr = 78105 Hz and fa = 79860
Hz for the 9mm long and for the 3mm long they are fr
= 78300 and fa = 80445. However, when the ceramics are
encapsulated in urethane, the water-isolation process sends
resonance to higher frequencies in the spectrum. Encapsulated
transducers show a frequency response with a continuous slope
of 180 and 300 Ω/octave respectively and lower impedance in
comparison to when they operate without any loading. Figure
3 also shows how a lower impedance can be achieved by
connecting hydrophones in parallel. This has the advantage
of increasing the directionality of the sensor at the expense of
higher driving power.
The passive sonar equation will be used as a model to
describe the acoustic system. Refer to ﬁgure 2 that represents
the energy path from transmission to reception, processing
and extraction of information from it. The ﬁrst event in the
communication process is the transmission of an acoustic
signal underwater by a projector. The tag transmits a 12ms
long sinusoidal signal centered at 51kHz. The user can select
among four transmission rates: 0.5, 1, 2 and 5 Hz. The
acoustic signal attenuates in water for two reasons: geometrical
spreading of the wave which is assumed to be spherical and
chemical energy absorption by the components of the sea. The
latter is speciﬁc to the conditions of the sea. The absorption
40 f0 60 fr fa 100
10
2
10
3
10
4
frequency (kHz)
Impedance(Ω)
Fig. 3. Transducers electrical response. (-×-) and (-.-) are 3mm and 9mm
long ring transducers respectively measured in air. (-*-) and (-◦-) represent
the same transducers after being water isolated in urethane. (-+-) Three 9mm
transducers connected in parallel show a lower impedance.
coefﬁcient (α) and therefore the transmission loss (TL) are
mostly affected by frequency [6].
The acoustic wavefront reaches the PZT sensor on the
receiving end at the surface. In addition to loss from atten-
uation, noise will add to the signal. The receiving voltage
sensitivity (RVS) of the transducer dictates how much voltage
can be measured from the transducer nodes in relation to
the pressure that is applied to it. A band pass ﬁlter with a
gain (G) of 60dB at 51kHz and a bandwidth of 2.5kHz was
implemented to increase the signal-to-noise ratio of the tag.
The ﬁlter was designed in three stages and implemented with
operational ampliﬁers OPA211 (Texas instruments). Tones are
detected by a LMC567 (National Semiconductor) integrated
circuit based on a phase-locked-loop (PLL). When the PLL
detects the presence of a signal in phase with the frequency
198

3.
of its internal voltage controlled oscillator, it locks onto it.
The PLL was tuned to detect 51kHz signals and the DC
output that it generates is timed by a microcontroller. In
order to conclude the effective transmission of the signal, tone
validation was implemented on the microcontroller: a detection
with a minimum duration of 10ms is valid; everything else is
discarded.
The detection scheme described above depends on the
amount energy within a frequency band that reaches the hy-
drophone. This bandwidth is determined by the quality factor
of the ﬁlters, the frequency response of the transducers and
the tone detector. These factors compose the sonar equation.
The minimum detection threshold (MDT) for the PLL circuit
is calculated as follows: MDT = SL - TL + RVS + G. The
tag’s source level (SL) was calculated to be 171 dB at 1m
when referenced to 1µPa. It was modeled as a thin walled
ring small in relation to the signal’s transmitted wavelength.
Similarly, the receiving voltage sensitivity (RVS) for the sensor
in the hydrophone was calculated as -212dB//1V/µ Pa. It is
possible to derive a relation between the MDT and acoustic
detection range by means of the TL = αR + 20log(R) and
determine the maximum distance at which a signal will reach
the receiver with enough energy to be detected.
III. RESULTS
The detection delay of the tone decoder depends on the
input SNR. If the order of arrival of an acoustic signal to
two or more hydrophones was to be determined, they would
have to be placed apart a distance equivalent to, at least,
the detection time times the sound speed in the water. In
an experiment, tones from a function generator were sent to
the analog processing circuit (ﬁgure 2.1) and detection delays
were measured. The mean detection delay was 78µs (n = 101),
which spatially means 12cm at a sound speed of 1546m/s. In
ﬁgure 4A the upper line represents the generated signal and the
lower line shows the digital decoder output. The input SNR to
the PLL is 21.7dB with respect to the 1.25Vp maximum that
the ﬁlters can achieve. The same measurements were made in
sheltered waters in the sea. The tag was installed 5m away
from the receiver, both at a depth of 1.5m with no obstacles
in between. The mean detection delay increased to 623µs (n =
101, SNR = 16dB) , i.e. a 96cm equivalent. (see ﬁgure 4B). A
minimum separation of 1m between hydrophones is required
to correctly detect the signal’s order of arrival.
The microcontroller timed the PLL’s active low digital
output from the falling to the raising edge. In-band noise would
interfere with the PLL and detections fail. This rendered a high
proportion of missed detections. The decoder was conﬁgured
to allow the largest bandwidth possible, i.e. the less restricted
detecting performance. The combination of both, detection
delay and detection unreliability reduced severely the detection
range of the hydrophone and tag previously described.
In another experiment, a hydrophone was installed 1m under
the surface, and the tag was towed away from it in 30m deep
water. Measurements were performed every 10m horizontally
and in each of these stations, the tag was lowered vertically
A
B
Fig. 4. A comparison between the PLL detection delay in lab conditions (A)
with SNR=21dB and in the sea (B) where SNR=16dB of maximum scale.
Enmarked are the results of a 100 trials experiment.
every 5m. The pinging rate of the tag was 2Hz and recordings
went on for a minute (120pings). The ping count of the
hydrophone was compared to 120 pings and a percentage of
detection calculated for each point (see ﬁgure 5). Interestingly,
there is a blind spot located under the sensor with an aperture
of about 45◦
. We have attributed this characteristic to the beam
pattern of the cylindrical transducer. Furthermore, detection
percentage drops considerably at a distance of 50m, which
differs considerably from the model.
To reduce this difference, several considerations need to
be taken into account. For example, in-situ measurements
of sea water characteristics could improve transmission loss
estimates. We expect a considerable adjustment of the model
output after calibrated measurements of the transducers sen-
sitivity and source level are performed. The reason behind
this lies in the fact that manufacturers characteristics differ
considerably from the operational characteristics and current
estimates are likely over estimating system’s performance.
In terms of detection, a matched ﬁlter is being studied
as an alternative to the process above described. For this
the signal received by a hydrophone is correlated against a
signal with known characteristics. Because the frequency of
the transmission is known, the correlator can be modeled
as a sinusoidal 51kHz 12ms signal. The correlation function
maximizes in the points where both, the received signal and
the correlator are more alike. The alternative is advantageous
because it provides an increased SNR output that depends on
199

4.
A
Fig. 5. Acoustic range of the hydrophone is represented as a percentage of
accurate detections performed on each of the recording points (marked with a
dot). Blue regions indicate zones were the hydrophone has trouble detecting
a source whereas warmer colors indicate a higher detection rate.
the amount of samples processed by the correlator [7]. An
additional beneﬁt is the fact that the correlated output for a
broad band signal, as opposed to that for a narrow band, has a
narrower detection peak. The relevance of this characteristic is
that the receivers can be located closer to each other while still
be able to determine correctly the order of arrival of a signal.
Figure 6 shows a comparison of both detection methods.
In this model a tag is put into two different scenarios:
10mVrms and a quieter 1mVrms white noise environment.
The output of the hydrophone’s signal processing circuit is
indicated with continuous lines in ﬁgure 6. This is the input
SNR for the decoder or, alternatively, for the correlation
function. The dotted lines in the same ﬁgure indicate the output
of a cross correlation between the hydrophone’s output and the
correlator described above. If a threshold of detection of 6dB is
used, like that indicated in the decoder datasheet, the detection
distance that can be achieved with this tag and hydrophone
is about 300m. However, the correlated output outperforms
energy-detection over the 150m distance. These are preliminar
results and research is ongoing to improve it.
IV. CONCLUSIONS
A microcontroller based underwater acoustic system was
described. A tag transmits 51kHz, 12ms sinusoidal tone into
the water. A ﬁlter with a band width of 2.5kHz and gain 30
processes the signal from a sensor in the hydrophone for a
7kHz phase-locked-loop tone detection circuit to detect it. The
passive sonar model indicates that on a -40dB//V white noise
environment, the circuit should be able to detect the signal at
approximately 1km. A mismatch in the signal, ﬁltering an tone
extraction frequency bands reduces the signal to noise ratio
and renders a high missed detection rate. Although the system
is capable of detecting the target signal by its frequency, its
range is sacriﬁced with the current architecture. A correlation
model indicates that the SNR can be increased over 30dB by
0 200 400 600 800 1000
−20
0
20
40
60
80
TonedetectionSNR(dB)
distance from source (m)
NL = −40dB, input
NL = −40dB, output
NL = −60dB, input
NL = −60dB, output
Fig. 6. The input SNR for a detection system is plotted in continuous lines.
The dotted lines show the output of the matched ﬁlter. The PLL minimum
SNR of 6dB is indicated for a reference.
using a matched frequency correlator, in addition to increasing
the system’s capability to detect broad band signals.
V. ACKNOWLEDGMENTS
Special thanks to E. Lloyd Smith for his support in the
development of the project.
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